Contractile units in disordered actomyosin bundles arise from F-actin buckling

Bundles of filaments and motors are central to contractility in cells. The classic example is striated muscle, where actomyosin contractility is mediated by highly organized sarcomeres which act as fundamental contractile units. However, many contractile bundles in vivo and in vitro lack sarcomeric organization. Here we propose a model for how contractility can arise in actomyosin bundles without sarcomeric organization and validate its predictions with experiments on a reconstituted system. In the model, internal stresses in frustrated arrangements of motors with diverse velocities cause filaments to buckle, leading to overall shortening. We describe the onset of buckling in the presence of stochastic actin-myosin detachment and predict that buckling-induced contraction occurs in an intermediate range of motor densities. We then calculate the size of the "contractile units" associated with this process. Consistent with these results, our reconstituted actomyosin bundles contract at relatively high motor density, and we observe buckling at the predicted length scale.Comment: 5 pages, 4 figures, Supporting text and movies attache

Insights Into the Evolution, Virulence and Speciation of Babesia MO1 and Babesia divergens Through Multiomics Analyses.

AbstractBabesiosis, caused by protozoan parasites of the genus Babesia, is an emerging tick-borne disease of significance for both human and animal health. Babesia parasites infect erythrocytes of vertebrate hosts where they develop and multiply rapidly to cause the pathological symptoms associated with the disease. The identification of new Babesia species underscores the ongoing risk of zoonotic pathogens capable of infecting humans, a concern amplified by anthropogenic activities and environmental changes. One such pathogen, Babesia MO1, previously implicated in severe cases of human babesiosis in the United States, was initially considered a subspecies of B. divergens, the predominant agent of human babesiosis in Europe. Here we report comparative multiomics analyses of B. divergens and B. MO1 that offer insight into their biology and evolution. Our analysis shows that despite their highly similar genomic sequences, substantial genetic and genomic divergence occurred throughout their evolution resulting in major differences in gene functions, expression and regulation, replication rates and susceptibility to antiparasitic drugs. Furthermore, both pathogens have evolved distinct classes of multigene families, crucial for their pathogenicity and adaptation to specific mammalian hosts. Leveraging genomic information for B. MO1, B. divergens, and other members of the Babesiidae family within Apicomplexa provides valuable insights into the evolution, diversity, and virulence of these parasites. This knowledge serves as a critical tool in preemptively addressing the emergence and rapid transmission of more virulent strains

Babesia duncani multi-omics identifies virulence factors and drug targets

Babesiosis is a malaria-like disease in humans and animals that is caused by Babesia species, which are tick-transmitted apicomplexan pathogens. Babesia duncani causes severe to lethal infection in humans, but despite the risk that this parasite poses as an emerging pathogen, little is known about its biology, metabolic requirements or pathogenesis. Unlike other apicomplexan parasites that infect red blood cells, B. duncani can be continuously cultured in vitro in human erythrocytes and can infect mice resulting in fulminant babesiosis and death. We report comprehensive, detailed molecular, genomic, transcriptomic and epigenetic analyses to gain insights into the biology of B. duncani. We completed the assembly, 3D structure and annotation of its nuclear genome, and analysed its transcriptomic and epigenetics profiles during its asexual life cycle stages in human erythrocytes. We used RNA-seq data to produce an atlas of parasite metabolism during its intraerythrocytic life cycle. Characterization of the B. duncani genome, epigenome and transcriptome identified classes of candidate virulence factors, antigens for diagnosis of active infection and several attractive drug targets. Furthermore, metabolic reconstitutions from genome annotation and in vitro efficacy studies identified antifolates, pyrimethamine and WR-99210 as potent inhibitors of B. duncani to establish a pipeline of small molecules that could be developed as effective therapies for the treatment of human babesiosis.We thank R. Gao for her contribution to the initial eforts to sequence the B. duncani genome. C.B.M.’s research was supported by grants from the National Institutes of Health (AI097218, GM110506, AI123321 and R43AI136118), the Steven and Alexandra Cohen Foundation (Lyme 62 2020), and the Global Lyme Alliance. S.L.’s research was supported by grants by the US National Science Foundation (IIS 1814359) and the National Institutes of Health (1R01AI169543-01). K.G.L.R.’s research was supported by the National Institutes of Allergy and Infectious Diseases (R01 AI136511, R01 AI142743-01 and R21 AI142506-01), the University of California, Riverside (NIFA-Hatch-225935) and the Health Institute Carlos III (PI20CIII/00037).S

Additive and interaction effects at three amino acid positions in HLA-DQ and HLA-DR molecules drive type 1 diabetes risk.

Variation in the human leukocyte antigen (HLA) genes accounts for one-half of the genetic risk in type 1 diabetes (T1D). Amino acid changes in the HLA-DR and HLA-DQ molecules mediate most of the risk, but extensive linkage disequilibrium complicates the localization of independent effects. Using 18,832 case-control samples, we localized the signal to 3 amino acid positions in HLA-DQ and HLA-DR. HLA-DQβ1 position 57 (previously known; P = 1 × 10(-1,355)) by itself explained 15.2% of the total phenotypic variance. Independent effects at HLA-DRβ1 positions 13 (P = 1 × 10(-721)) and 71 (P = 1 × 10(-95)) increased the proportion of variance explained to 26.9%. The three positions together explained 90% of the phenotypic variance in the HLA-DRB1-HLA-DQA1-HLA-DQB1 locus. Additionally, we observed significant interactions for 11 of 21 pairs of common HLA-DRB1-HLA-DQA1-HLA-DQB1 haplotypes (P = 1.6 × 10(-64)). HLA-DRβ1 positions 13 and 71 implicate the P4 pocket in the antigen-binding groove, thus pointing to another critical protein structure for T1D risk, in addition to the HLA-DQ P9 pocket.This research utilizes resources provided by the Type 1 Diabetes Genetics Consortium, a collaborative clinical study sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Allergy and Infectious Diseases (NIAID), National Human Genome Research Institute (NHGRI), National Institute of Child Health and Human Development (NICHD), and Juvenile Diabetes Research Foundation International (JDRF) and supported by U01 DK062418. This work is supported in part by funding from the National Institutes of Health (5R01AR062886-02 (PIdB), 1R01AR063759 (SR), 5U01GM092691-05 (SR), 1UH2AR067677-01 (SR), R01AR065183 (PIWdB)), a Doris Duke Clinical Scientist Development Award (SR), the Wellcome Trust (JAT) and the National Institute for Health Research (JAT and JMMH), and a Vernieuwingsimpuls VIDI Award (016.126.354) from the Netherlands Organization for Scientific Research (PIWdB). TLL was supported by the German Research Foundation (LE 2593/1-1 and LE 2593/2-1).This is the accepted manuscript. The final version is available at http://www.nature.com/ng/journal/v47/n8/full/ng.3353.html

A microscopy-based screen employing multiplex genome sequencing identifies cargo-specific requirements for dynein velocity

The timely delivery of membranous organelles and macromolecules to specific locations within the majority of eukaryotic cells depends on microtubule-based transport. Here, we describe a screening method to identify mutations that have a critical effect on intracellular transport and its regulation using mutagenesis, multicolor-fluorescence microscopy, and multiplex genome sequencing. This screen exploits the filamentous fungus Aspergillus nidulans, which has many of the advantages of yeast molecular genetics, but uses long-range microtubule-based transport in a manner more similar to metazoan cells. Using this method, we identified 7 mutants that represent novel alleles of components of the intracellular transport machinery: specifically, kinesin-1, cytoplasmic dynein, and the dynein regulators Lis1 and dynactin. The two dynein mutations identified in our screen map to dynein's AAA+ catalytic core. Single-molecule studies reveal that both mutations reduce dynein's velocity in vitro. In vivo these mutants severely impair the distribution and velocity of endosomes, a known dynein cargo. In contrast, another dynein cargo, the nucleus, is positioned normally in these mutants. These results reveal that different dynein functions have distinct velocity requirements

Erasing Sensorimotor Memories via PKMζ Inhibition

Sensorimotor cortex has a role in procedural learning. Previous studies suggested that this learning is subserved by long-term potentiation (LTP), which is in turn maintained by the persistently active kinase, protein kinase Mzeta (PKMζ). Whereas the role of PKMζ in animal models of declarative knowledge is established, its effect on procedural knowledge is not well understood. Here we show that PKMζ inhibition, via injection of zeta inhibitory peptide (ZIP) into the rat sensorimotor cortex, disrupts sensorimotor memories for a skilled reaching task even after several weeks of training. The rate of relearning the task after the memory disruption by ZIP was indistinguishable from the rate of initial learning, suggesting no significant savings after the memory loss. These results indicate a shared molecular mechanism of storage for declarative and procedural forms of memory

A search for photometric variability towards M71 with the Near-Infrared Transiting ExoplanetS Telescope

We present the results of a high-cadence photometric survey of an 11 arcmin × 11 arcmin field centred on the globular cluster M71, with the Near-Infrared Transiting ExoplanetS Telescope. The aim of our survey is to search for stellar variability and giant transiting exoplanets. This survey differs from previous photometric surveys of M71 in that it is more sensitive to lower amplitude (ΔM ≤ 0.02 mag) and longer period (P > 2 d) variability than previous work on this cluster. We have discovered 17 new variable stars towards M71 and confirm the nature of 13 previously known objects, for which the orbital periods of 7 are refined or newly determined. Given the photometric precision of our high-cadence survey on the horizontal branch of M71, we confirm that the cluster is devoid of RR Lyrae variable stars within the area surveyed. We present new B- and V-band photometry of the stars in our sample from which we estimate spectral types of the variable objects. We also search our survey data for transiting hot Jupiters and present simulations of the expected number of detections. Approximately 1000 stars were observed on the main sequence of M71 with sufficient photometric accuracy to detect a transiting hot Jupiter; however, none were found

Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning

IntroductionOrgan-at-risk segmentation for head and neck cancer radiation therapy is a complex and time-consuming process (requiring up to 42 individual structure, and may delay start of treatment or even limit access to function-preserving care. Feasibility of using a deep learning (DL) based autosegmentation model to reduce contouring time without compromising contour accuracy is assessed through a blinded randomized trial of radiation oncologists (ROs) using retrospective, de-identified patient data.MethodsTwo head and neck expert ROs used dedicated time to create gold standard (GS) contours on computed tomography (CT) images. 445 CTs were used to train a custom 3D U-Net DL model covering 42 organs-at-risk, with an additional 20 CTs were held out for the randomized trial. For each held-out patient dataset, one of the eight participant ROs was randomly allocated to review and revise the contours produced by the DL model, while another reviewed contours produced by a medical dosimetry assistant (MDA), both blinded to their origin. Time required for MDAs and ROs to contour was recorded, and the unrevised DL contours, as well as the RO-revised contours by the MDAs and DL model were compared to the GS for that patient.ResultsMean time for initial MDA contouring was 2.3 hours (range 1.6-3.8 hours) and RO-revision took 1.1 hours (range, 0.4-4.4 hours), compared to 0.7 hours (range 0.1-2.0 hours) for the RO-revisions to DL contours. Total time reduced by 76% (95%-Confidence Interval: 65%-88%) and RO-revision time reduced by 35% (95%-CI,-39%-91%). All geometric and dosimetric metrics computed, agreement with GS was equivalent or significantly greater (p<0.05) for RO-revised DL contours compared to the RO-revised MDA contours, including volumetric Dice similarity coefficient (VDSC), surface DSC, added path length, and the 95%-Hausdorff distance. 32 OARs (76%) had mean VDSC greater than 0.8 for the RO-revised DL contours, compared to 20 (48%) for RO-revised MDA contours, and 34 (81%) for the unrevised DL OARs.ConclusionDL autosegmentation demonstrated significant time-savings for organ-at-risk contouring while improving agreement with the institutional GS, indicating comparable accuracy of DL model. Integration into the clinical practice with a prospective evaluation is currently underway